芒果面积、产量和产值的统计建模与预测

IF 0.1 Q4 AGRICULTURE, MULTIDISCIPLINARY
G. M. Naidu, S. G. Rao
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引用次数: 0

摘要

本研究旨在预测和分析 1991-1992 年至 2017-2018 年期间安得拉邦芒果作物的种植面积、产量和收益趋势。研究采用了不同的非线性模型和 ARIMA 模型来预测和分析面积、产量和单产趋势。用于预测安得拉邦芒果作物产量和单产的立方模型和用于预测面积趋势的幂模型都很好地贴合了数据。根据调整后的 R2、RMSE 和 MAE 等模型选择参数,预测芒果面积、产量和单产的最佳模型是 ARIMA (2,0,2)、立方模型和 ARIMA (2,2,1)。研究结果表明,安得拉邦芒果作物的产量、生产量和种植面积在未来几年可能会呈上升趋势。预计 2022-2023 年的芒果面积约为 64.1 万公顷,产量约为 656.5 万公吨,芒果产量约为 45.4 公吨/公顷。面积与芒果产量之间呈非显著正相关。关键词:增长率、非线性、ARIMA 模型、Ljung-Box Q 检验、2 R、RMSE、MAE 和相关性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Statistical Modeling and Forecasting of Area, Production and Yield of Mango
The goal of the current study was to forecast and analyze the trends in the area, production and yield of mango crops planted in Andhra Pradesh between 1991-1992 and 2017-2018. Different non-linear and ARIMA models were used to forecast and analyse area, production, and yield trends. The cubic model for production and yield of the mango crop farmed in Andhra Pradesh and the Power model for area trends both fit the data well. For forecasting mango area, production and yield, the best models were ARIMA (2,0,2), Cubic and ARIMA (2,2,1) based on model selection parameters such as adjusted R2 , RMSE, and MAE. The findings showed that the yield, production and area of the growing mango crop in Andhra Pradesh would likely exhibit an upward trend in the future years. The projected figures for 2022-2023 were roughly 641 thousand hectares of mango area, 6565 thousand metric tonnes of production and 45.4 mt/ha of mango crop yield. A non-significant positive correlation was found between the area and mango yield.. KEYWORDS :Growth rates, Non-linear, ARIMA models, Ljung-Box Q test, 2 R , RMSE, MAE and Correlation.
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66.70%
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4
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